One of the most valuable assets of a company, if not the most critical one, is its intellectual capital which, among other things, includes human assets. A company can maximize its intellectual capital only if it understands its key elements and how these elements interact with each other to add value to the company. Understanding the nature of the interactions between these elements can reveal significant information about and for the company. More and more companies today acknowledge the importance and relevance of such interactions, and allocate significant resources to analyze and utilize these interactions. Successful companies manage to extend these interactions well beyond the company boundaries by analyzing interactions with customers, partners, suppliers and alliances as well. Essentially, such interactions, whether explicit or implicit, define specialized human networks with complex organizational dynamics.
While the importance of human networks is well understood for effective organizational management, existing methodologies by which such networks can be analyzed are not well-defined. Existing methodologies generally rely on statistical sampling and/or informal opinion polling techniques which are neither complete nor reliable. Typically, they are ad hoc and do not include the entire target population in analyses. Also, existing methodologies focus on qualitative rather than quantitative analyses of organizational interactions.
Furthermore, at present, the only way to display interactions among entities that is known to the inventor is the brute-force documentation of interactions in either a spreadsheet or a directed graph structure. “Entity” as used herein includes individuals as well as groups, such as a department within a corporation. Directed graphs function by explicitly linking entities and while typically easier to understand and glean information from than spreadsheets, are not satisfactory as the number of entities and the number of interactions increase.
What is desired, therefore, is a graphical approach that overcomes the disadvantages of the existing graphical approaches and provides a compact, multi-level interaction context from which desired information can be gleaned expeditiously.